Title: Detecting and characterising of mobile advertisement network traffic using graph modelling

Authors: Hiroki Kuzuno; Kenichi Magata

Addresses: SECOM Co., Ltd., Shibuya-ku, Tokyo 150-0001, Japan ' Intelligent Systems Laboratory, SECOM Co., Ltd., Mitaka, Tokyo 181–8528, Japan

Abstract: Many 'free' applications are provided for Android. These include advertisement (ad) modules manage ad services and track user sensitive behaviour. These sometimes lead violations of privacy. We analysed 797 of 1,188 applications included 45 known ad modules and found characteristic ad network traffic patterns. In order to accurately differentiate traffic between ad modules and valid application, we propose a novel method based on the distance between traffic graphs mapping the relationships between HTTP sessions. Using this method, we can detect ad modules' traffic by comparing session graphs with known ad graphs. In evaluation, we generated 20,903 graphs from applications traffic includes 4,698 known ad graphs, manually identified 2,000 ad graphs, and 2,000 standard application graphs. We also evaluated graph screening for detection accuracy. Our approach showed 76% detection rate for known ad graphs, 96% detection rate for manually classified ad graphs, and under 10% false positive rate for standard graphs.

Keywords: security; privacy; Android; mobile networks; graph modelling; mobile advertising; network traffic; mobile adverts; advertisement modules; ad modules.

DOI: 10.1504/IJSSC.2016.077971

International Journal of Space-Based and Situated Computing, 2016 Vol.6 No.2, pp.90 - 101

Received: 19 Nov 2015
Accepted: 13 May 2016
Published online: 28 Jul 2016 *

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